1. Technical Field
The present invention generally relates to computer-assisted diagnosis (CADx) and, in particular, to an interactive computer-aided diagnosis (ICAD) method and system for assisting diagnosis of lung nodules in digital volumetric medical images.
2. Background Description
Computer-Aided diagnosis (CADx) is an important technology in many clinical applications, such as the detection of lung cancer. In current clinical practice, cancer or other diseases may be missed during a physician's un-aided examination of medical image data, in part because of the large volume of data. This is particularly a problem for screening applications, since there is generally little time to devote to the examination of each patient's data, and the entire range of the data must be examined to make sure it is free from disease. Computer analysis that is performed silently in the background can greatly aid physicians in their work.
New technologies that offer three-dimensional (3-D) scans of the human body, such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), offer tremendous opportunities for improved detection of disease. However the change from two dimensions to three, especially to large volume 3-D data (such as image volumes produced by multi-detector high resolution CT scanners), results in a much larger amount of data for the physician to examine. Furthermore, the low-dose imaging for cancer screening poses additional challenges to the traditional manual clinical reading. Thus, the assistance of computer analysis becomes even more important.
Unfortunately, many current CADx systems are not readily accepted by physicians, because their aid is seen as more of a distraction than a help. Many such systems present the results of the computer's diagnosis to the physicians by marks, such as a red circle or arrow on the softcopy, which some physicians believe can create a bias in their interpretation of the data. Furthermore, too many systems are perceived as a “black box”, where physicians feel they do not have any understanding of how such systems work and how they generate their diagnoses.
Accordingly, it would be desirable and highly advantageous to have a CADx system that is an “open box”, increasing its acceptance among physicians.